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mlmentorship
mlmentorship field guide2026 edition

Visual-first · senior to principal

The ML Interview Field Guide

See the state, decision, and tradeoff behind senior ML interview answers.

390 visual lessons · 10 ordered books · free to read

Start here

Choose the shortest route from what you already know.

You do not need to read the library front to back.

Active interview loop? Build a private plan from your role, rounds, available time, and recent evidence. It stays in this browser.

The curriculum

10 books, ordered from foundations to interview execution.

Open a shelf, then choose a book or start its first visual.

Core MLBuild the technical base used across applied, research, and engineering interviews.
  1. I

    ML foundations

    Math, probability, classical machine learning, deep learning, and the core questions that test them.

    9 chapters · 62 entries
  2. II

    Model training and research

    Optimization, reliable experiments, implementation, debugging, and research judgment.

    9 chapters · 52 entries
  3. III

    Evaluation and product ML

    Metrics, experimental validity, calibration, product decisions, and production evaluation.

    4 chapters · 25 entries
Frontier AI systemsStudy language models, post-training, agents, accelerators, and distributed systems.
  1. IV

    LLMs, agents, and post-training

    Transformer internals, inference, retrieval, evaluation, agents, alignment, and post-training.

    7 chapters · 42 entries
  2. V

    ML systems and infrastructure

    Accelerators, distributed training, inference systems, reliability, cost, and full ML architecture.

    6 chapters · 30 entries
Specialist tracksAdd only the specialist subject required by the role and team.
  1. VI

    Retrieval, ranking, and recommendations

    Embeddings, candidate generation, ranking, search metrics, cold start, and feedback loops.

    4 chapters · 23 entries
  2. VII

    Reinforcement learning and robotics

    Sequential decisions, value and policy methods, environments, rewards, and robotics policy learning.

    3 chapters · 13 entries
  3. VIII

    Vision, language, and speech

    Visual models, multimodal systems, sequence modeling, natural language, and speech.

    4 chapters · 21 entries
Interview executionPrepare role choice, project evidence, behavioral judgment, and senior-level communication.
  1. IX

    Interview and career practice

    Role choice, level calibration, project stories, behavioral judgment, and long-form field guides.

    3 chapters · 15 entries
  2. X

    Coding interview practice

    A visual-first coding field guide for data structures, algorithms, and practical AI coding. Learn each problem by seeing the state it preserves, the move it makes, and the invariant that makes the move safe.

    11 chapters · 107 entries
Built from practice

Specific, current, and honest about scope.

Written by Hamidreza Saghir, Principal Applied Scientist at Microsoft, with earlier ML engineering, applied-science, and research roles at X, Amazon, and Borealis AI. The site uses public process evidence, never leaked prompts or job-outcome promises. About the author and project.